Job Description

Key Responsibilities



Lead research in rapid simulations, optimisation algorithms, and AI-enhanced workflows for enterprise multi-resource planning, primarily for the topics of production scheduling, operation planning, capacity planning, and sourcing and inventory analytics. Design practical algorithms to solve industry-inspired operational problems, performing solution benchmarking and discover novel market leading algorithms. Work with research engineers to translate research outcomes into deployable solutions for industrial applications. Formulate cutting edge scientific research directions and develop innovative research / project proposals aligned with industry needs. Drive competitive research funding proposals and collaborations with industry and academic partners (IHLs, other research institutes etc.). Contribute to the development of ARTC?s R&D roadmap in enterprise optimisation. Publish at leading international academic or industrial journals and conferences to contribute ASTAR's reputation as a leading R&D organisation.
Mentor junior researchers in scientific methods and research professionalism.

Requirements



PhD in AI, Computer Science, Operations Research, or related disciplines with a clear emphasis on simulation, optimisation, machine learning, or data science. Deep understanding of production scheduling, operations planning, capacity planning, or sourcing & inventory analytics in the context of manufacturing. Strong background in modelling (e.g. discrete-event simulations), numerical optimisation (exact methods, meta-heuristics, surrogate-model-assisted methods) and AI as applied to solving various operations research problems. Experience with industry problems under real-world conditions is particularly sought after. 3+ years of experience in post-PhD research. Demonstrated leadership or project management in relevant areas. Experience in managing project delivery teams would be highly advantageous. Proven expertise in programming and algorithm development in Python (with all the associated data science and optimisation libraries). C# .NET, software engineering, and productisation experience would be advantageous. A track record of publications in top-tier journals and conferences. Excellent verbal and written communication skills, adaptable to various technical and non-technical contexts: research conferences, business presentations, and software development teams. Positive, proactive attitude, with the ability to influence and collaborate effectively across multiple stakeholders.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

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